Genetic Relationships of Puccinia striiformis f. sp. tritici in Southwestern and Northwestern China

ABSTRACT Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a crucial disease for wheat worldwide and constantly threatens wheat production in southwestern and northwestern China, where the environment is a good fit for Pst oversummering and overwintering. However, the underlying genetic dynamics of spring epidemic Pst populations across large areas of continuous planting in the southwestern and northwestern regions are poorly understood. A total of 2,103 Pst isolates were sampled in the spring of 2019 from the two agroecosystems and grouped into three horizontal spatial scales (countywide, provincial, and regional subpopulations) and two vertical spatial scales that consisted of elevational and geomorphic subpopulations. A total of 776 multilocus genotypes were identified, with the highest genetic diversity found in the northern and Sichuan populations, particularly in the Ningxia and Sichuan Basins, while the lowest genetic diversity was found in the Yunnan and Guizhou populations. Multivariate discriminant analysis of principal components (DAPC) and STRUCTURE (STRUCTURE 2.3.4) analyses revealed variation in the genotypic compositions of the molecular groups on horizontal and vertical dimensions from north to south or vice versa and from low to high or vice versa, respectively. The regional neighbor-joining tree revealed three large spatial structures consisting of the southwestern, the northwestern, and the Xinjiang regions, while the Tibetan population connected the southwestern and northwestern regions. The isolates of the Sichuan Basin were scattered over the four quartiles by principal coordinate analysis, which indicated frequent genotype interchange with others. Greater genetic differentiation was observed between the southwestern and northwestern regions. Linkage equilibrium (P ≥ 0.05) was detected on different spatial scales, suggesting that Pst populations are using sexual reproduction or mixed reproduction (sexual and clonal reproduction) in southwestern and northwestern China. IMPORTANCE Understanding the epidemiology and population genetics of plant pathogens is crucial to formulate efficient predictions of disease outbreaks and achieve sustainable integrated disease management, especially for pathogens with migratory capability. Here, this study covers the genetic homogeneity and heterogeneity of different geographical Pst populations on broad to fine spatial scales from the key epidemic regions of the two agroecosystems in China, where wheat stripe rust occurs annually. We provide knowledge of the population genetics of Pst and reveal that, for instance, there is greater genetic diversity in northwestern China, there are close genetic relationships between Yunnan and Guizhou and between Gansu-Ningxia and Qinghai, and there are effects of altitude on genetic compositions, etc. All of these findings clarify the genetic relationships and expand the insights into the population dynamics and evolutionary mechanisms of Pst in southwestern and northwestern China, providing a theoretical basis for achieving sustainable control of wheat stripe rust in key epidemic regions.

Please noticed that the comments present in the following were based on the document named 278085_0_ 278085_0_merged_1651065866.pdf from review system. 1. Lots of abbreviation were employed in the Figs, so each abbreviation should be list in each figure information or add the summary including all abbreviations at the front or end of manuscript. 2. For consistency, the legend presented as 1,2,3 might be replaced as cluster 1, cluster 2, cluster3 in fig2. 3. The fig4B-4C, the values in the branch should be improved via reducing the font size. 4. The values showed at bottom left in Fig5 should be shifted to the bottom of each roundness and it can be realized via Adobe Illustrator. 5. The table1 should be transfer in the additional files. 6. The original title is general or ambiguous, it should be revealed the major results or conclusion to increase attractiveness. Such as, the genetic diversity characterization of Puccinia striiformis f. sp. tritici in southwestern and northwestern China with 2103 isolates or The genetic diversity of Pst in Puccinia striiformis f. sp. tritici provide new insights into the population dynamics and evolutionary mechanisms of Pst in southwestern and northwestern China. These two titles are just suggestion and the final title should be confirmed by the authors and editors. 7. Line 23-26, it is suggested to modified as Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici, is an important disease for wheat worldwide and constantly threaten wheat production in southwestern or northwestern of China where the areas fit for Pst oversummering and overwintering in China. 8. Abbreviations were not suggested in the abstract. 9. Line 81-83, is this the previous research about the potential oversummering or overwintering aeras of Pst in China? If yes, please add their result or conclusion. 10. Line 104-118, the description should be summarized and rewrite, the results from the references were simple presented by publish years and this is not professional. 11. Line 156-162, the highest and lowest regions and their diversity index should be presented. 12. The total name of EHM was not list when firstly described in the manuscript. 13. Line189-194, line 311-316 and line 327-333 might be included in the discussion. 14. Line 332-333, there was no sexual reproduction in Group L, why? The reason could be discussed in the discussion. 15. The figure7 was suggested to listed in the supplemental flies. 16. As the focused on the oversummering and overwintering areas, could you furtherly inference or discuss the epidemic pathway of Pst in these areas or Chinese regions? This might be contributed to study population dynamics and evolutionary mechanisms of Pst. 17. Line 543, Liang (2013) should be removed. 18. If the program or reaction system were same with your previous study, please curtrail line 554-569 as citing a reference. 19. The software and statistics method used in Fig S1 should be revised in the materials and methods. 20. In table S1, the longitude and latitude of sample areas should be better added. This is optional and not necessary. 21. Finally and importantly, all language, include the description of figures, must be improved and modified by naïve academic editor.
Reviewer #2 (Comments for the Author): Manuscript #Spectrum01530-22 investigated the genetic relationship of Pst in southwest and northwest of China. More than 2000 Pst samples across major provinces in western China were analyzed from horizontal (i.e., County, provincial and regional subspecies) and vertical (i.e., altitude and geomorphic subspecies). The finding in the study should be useful in dissect the epidemics of stripe rust in China. However, some concerns should be addressed. Major concerns: 1. The authors classified Pst samples into different groups according to different criteria, such as country, province, region, elevation, and landform, which is good for systematical analysis. However, it seems the other groups (E, R, L) are the subgroups of Group P displayed in Table S1. So, it is questionable that classifying the isolates simply by elevation or other single factor is meaningful in the study. 2. In this case, it is hard to understand why the isolates collected from Xinjiang and Shaanxi are excluded in Group P, but are included in Group R, E and L. 3. Elevation is the only factor taken into consideration for Group E and R, so it is better to combine these two groups. 4. In the Line 624, the authors mentioned the K clusters from 1 to 10. In fact, the cluster in the manuscript should be ranged from 2 to 9 as shown in Fig. 2. Also, analyses at higher K (5 to 10) could provide a better interpretation in the complicated population. 5. The connection between text and tables/figure is lacking. For example, QH, SC, NX, QH, CQ, GZ, XZ, and PL in the Line 157 and 159 cannot be found in corresponding tables. 6. It is hard to interpretate result in the genetic differentiation analysis in Group E displayed in Fig. 5C. More information should be provided in the Figure. Based on the results, the authors mentioned "The highest value (Gst=0.254) was between 2.8-3.0K and 1.0-1.2K". Why the highest Gst is not between 0-0.2K to 3.0-3.2K? 7. Grammatical errors and ambiguous descriptions impair the quality of the manuscript, such as Line 50-55, 63-64, 66-67, 92-94, 122-125 in the introduction part. The authors should also check and revise the statements in other parts. Minor concerns: 1. The author should connect different studies in the line 104 to 118 instead of listing all the results. 2. Provide the accurate P value in the Fig. 7, and keep all the "P" Italic. 3. Improve the quality of Fig. 5 to make every number readable.
Reviewer #3 (Comments for the Author): Comments 1.Several decades research discovered four over-summering areas in China, namely northwestern, south-western, Xinjiang, and northern over-summering regions. The NW and SW regions are the largest and the most important over-summering areas in China, so, it is vital to study the genetics of Pst in the SW and NW regions to improve the management of WSR in China. However, we can't see any sampling strategy from the manuscript, which is crucial to draw a right conclusion. Table S1, for Xingjiang and Shaanxi, the samples less than 20, and just from one county, one cultivar. For Ningxia and Gansu, althrough the samples more than 20, even more than 100, but it from one county. For the four provinces, the representativeness is questionable, can't meet the requirement of statistic. Althrough the authors remove the Xingjiang and Shaanxi isolates when analyzed the genetic diversity data at the provincial level (Group P), but included as a part in Group R, E, and L. Even though at regional level, samples only from one cultivar and less than 20 samples can't represent a region. Therefore, related results like Xingjiang is of greatest genetic variation compared with other regions, is questionable. Few samples can provide some clues, but to draw a conclusion should be prudential.

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3.Too much tables and figures, so need to be simplified. For Table 1 can be removed or list as supplemental table for it has been publish before. In Fig. 2 and 3, listed K=2, k=3, respectively. To my knowledge, just one K value is most appropriate, which one? Select it and remove another. For Fig.7, as R2 less that 0.03, very low, no need to make the figure, just mention it in the text. In Fig. 1(A,B,C) , 6, and Table 2A,2B,3A,3B, "19S" in all words contained can be removed as all samples collected in 2019 spring, no need to mention always, it looks very prolix.
4.In Fig. 1 C, what's the meaning of the abbreviation of "ZSE" etc. ? In Fig. 1  5.Line 37-38, from the Abstract, the authors wrote "The regional neighbor-joining tree presented three big spatial structures, SW, NW, and Xinjiang", which has been concluded by previous epidemiological study, this work just confirmed the well-known theory, seems have no any new findings.
6.Line 157, QH appeared twice, should be mistakes. And what is the difference between genotypic diversity and gene diversity? 5.Line 554-566, In Materials and Methods part -SSR amplification, for all 12 markers, the reaction condition is similar only the annealing temperature classified as 56℃ and 52℃. The statement seemed too prolix, it can be simplified.

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Thank you for submitting your paper to Microbiology Spectrum.   20. In table S1, the longitude and latitude of sample areas should be better added. This is optional and not necessary.
21. Finally and importantly, all language, include the description of figures, must be improved and modified by naïve academic editor.

Dear editors,
We appreciate your and other three reviewers' work. We revised the manuscript according to the reviewers' comments one by one, and the details as following: Reviewer #1 16. This paper mainly focus on the genetic relationship of Pst in southwestern and northwestern China, the epidemic pathway is other theme, we will analysis this theme by other methods in the next one paper.
18. We deleted the details, and added the corresponding reference.
19. We added the statistics method of Fig. S1 in the materials and methods. 20. In Table S1, we unable to added the longitude and latitude because of too many sampling sites, if we do this, the Table S1 will be too long. 21. We improved and modified all language in the text.
Reviewer #2 (Comments for the Reviewer): 1. In Table S1, in order to present the sampling and grouping relationships more comprehensively, so we put all the information together, there's no dependencies among the different spatial scale subpopulations, if we deal different spatial scales subpopulations to differ Tables, that's lead to too many Tables. In this analysis, the reason why we used single factor to classify isolates is we try to find the Pst under grand space in southwestern and northwestern China, whether existed inner correlation between genetic relationship and geography, whatever horizontal and vertical dimensions.
2. It's meaningless to analyze the genetic diversity if a population only contained one subpopulation, otherwise more than one subpopulation. In this research, the Xinjiang population is only one subpopulation on provincial and regional spatial scales. Shaanxi population only counted in Group R as one of two subpopulations. We revised the sentence as: Due to less than three sampling villages or sites, the isolates from Xinjiang province were excluded during the genetic diversity analysis at the provincial and regional levels (Group P and Group R) but included as a part in Group E and L, as well as Shaanxi population was excluded on provincial level but included as a part in Group R, E, and L.
3. In this paper, we used two different vertical spatial scales, variated from relative broader to finer-spatial scale on vertical dimension, that could better to explicit the genetic relationship of Pst populations in southwestern and northwestern China. 4. We revised the values of K in Fig.2 ranged from 2 to 9. We used non-parametrical and parametrical models to assess best K values both were 2, so we haven't analyzed the population structure when K ranged from 5 to 10.  Table 2A. 6. The result of genetic differentiation on elevational level revealed the correlation between genetic differentiation and elevation was no standard linear increase, it meant the highest genetic differentiation maybe not existed between subpopulations 0-0.2K and 3.0-3.2K, however, we can find that the relative higher genetic differentiation always occurred between altitude higher than 2,000m and lower than 2,000m. In addition, the result of Group L confirmed this conclusion.